Certificate verification

ABSTRACT

A computer-implemented certificate verification method includes: obtaining, by a certificate verification module, at least two images of a certificate, in which the at least two images are acquired under different acquisition conditions; obtaining, from the at least two images, at least two target images that correspond to respective images of the at least two images and that each include an image of a light-reflective coating of the certificate; and determining, based on the at least two target images, a probability that the certificate is an original.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of and claims the benefit of priorityof U.S. patent application Ser. No. 17/164,578, filed Feb. 1, 2021,which is a continuation of and claims the benefit of priority of U.S.patent application Ser. No. 16/945,778, filed Jul. 31, 2020, which is acontinuation of and claims the benefit of priority of U.S. patentapplication Ser. No. 16/807,914, filed Mar. 3, 2020, now U.S. Pat. No.10,769,263, which is a continuation of PCT Application No.PCT/CN2020/071608, filed on Jan. 12, 2020, which claims priority toChinese Patent Application No. 201910374005.3, filed on May 7, 2019, andeach application is hereby incorporated by reference in their entirety.

TECHNICAL FIELD

The present specification relates to the field of computer technologies,and in particular to methods, apparatuses, and devices for certificateverification and identity verification.

BACKGROUND

During Know Your Customer (KYC) electronic real-name authentication,users usually need to photograph identity certificates (such as identitycards, passports, etc.) and upload photos. However, the photographingprocess may not be effectively monitored. For example, it may not bedetermined whether the photographed identity certificate is an original,and whether the photographed identity certificate is legally held,leaving vulnerability for attackers (also referred to as black industryusers). In other words, black industry users can photograph forgedcertificates to obtain photos to be uploaded, thereby deceiving theelectronic authentication process. The methods for forging certificatesby black industry users usually include forging a physical certificateand forging an electronic certificate. Forging a physical certificaterefers to modifying information directly on a physical entity of anoriginal certificate, for example, altering content (such as a name, acertificate number, etc.) on a surface of the certificate, pasting andcovering the content (such as a portrait photo, a certificateidentifier, etc.) on the surface of the certificate. Forging anelectronic certificate refers to first digitizing an originalcertificate through photographing, scanning, etc., then alteringinformation on an obtained digitized certificate image by using an imageprocessing tool, and finally presenting the forged electroniccertificate physically (for example, on a screen or by printing).

SUMMARY

In view of the previous description, embodiments of the presentspecification provide methods, apparatuses, and devices for certificateverification, to verify authenticity of a certificate during electronicauthentication. Embodiments of the present specification further providemethods, apparatuses, and devices for identity verification, to verifyan identity based on authenticity of a certificate during electronicauthentication.

The following technical solutions are used in the embodiments of thepresent specification:

An embodiment of the present specification provides a certificateverification method, including the following: acquiring at least twoimages of a to-be-verified certificate, where the at least two imagesare images obtained by performing image acquisition on theto-be-verified certificate under different acquisition conditions;obtaining, from the at least two images, a target image(s) thatcorresponds to the at least two images and that includes a coatingfeature, where the coating feature includes an image feature of alight-reflecting characteristic of a coating of the to-be-verifiedcertificate in a corresponding image; and determining, based on thetarget image(s) corresponding to the at least two images, a probabilitythat the to-be-verified certificate is an original.

An embodiment of the present specification further provides an identityverification method, including the following: acquiring at least twoimages of an identity certificate of a to-be-verified object, where theat least two images are images obtained by performing image acquisitionon the identity certificate under different acquisition conditions;obtaining, from the at least two images, a first target image(s) thatcorresponds to the at least two images and that includes a coatingfeature, where the coating feature includes an image feature of alight-reflecting characteristic of a coating of the identity certificatein a corresponding image; determining, based on the first targetimage(s) corresponding to the at least two images, a probability thatthe identity certificate is an original; when it is determined that theidentity certificate is an original based on the probability, obtaininga second target image(s) that includes identity information from one ofthe at least two images; verifying the identity information in thesecond target image(s) online to determine authenticity of the identityinformation; and determining authenticity of the identity of theto-be-verified object based on the authenticity of the identityinformation.

An embodiment of the present specification further provides acertificate verification apparatus, including an image acquisitionmodule, an acquisition module, and a verification module, where theimage acquisition module is configured to acquire at least two images ofa to-be-verified certificate, where the at least two images are imagesobtained by performing image acquisition on the to-be-verifiedcertificate under different acquisition conditions; the acquisitionmodule is configured to obtain, from the at least two images, a targetimage(s) that corresponds to the at least two images and that includes acoating feature, where the coating feature includes an image feature ofa light-reflecting characteristic of a coating of the to-be-verifiedcertificate in a corresponding image; and the verification module isconfigured to determine, based on the target image(s) corresponding tothe at least two images, a probability that the to-be-verifiedcertificate is an original.

An embodiment of the present specification further provides an identityverification apparatus, including an image acquisition module, a firstacquisition module, a first verification module, a second acquisitionmodule, a networking module, and a second verification module, where theimage acquisition module is configured to acquire at least two images ofan identity certificate of a to-be-verified object, where the at leasttwo images are images obtained by performing image acquisition on theidentity certificate under different acquisition conditions; the firstacquisition module is configured to obtain, from the at least twoimages, a first target image(s) that corresponds to the at least twoimages and that includes a coating feature, where the coating featureincludes an image feature of a light-reflecting characteristic of acoating of the identity certificate in a corresponding image; the firstverification module is configured to determine, based on the firsttarget image(s) corresponding to the at least two images, a probabilitythat the identity certificate is an original; the second acquisitionmodule is configured to: when it is determined that the identitycertificate is an original based on the probability, obtain a secondtarget image(s) that includes identity information from one of the atleast two images; the networking module is configured to verify theidentity information in the second target image(s) online to determineauthenticity of the identity information; and the second verificationmodule is configured to determine authenticity of the identity of theto-be-verified object based on the authenticity of the identityinformation.

An embodiment of the present specification further provides acertificate verification electronic device, including the following: atleast one processor; and at least one memory communicatively connectedto the at least one processor, where the memory stores an instructionthat can be executed by the at least one processor, and the instructionis executed by the at least one processor to enable the at least oneprocessor to perform the following operations: acquiring at least twoimages of a to-be-verified certificate, where the at least two imagesare images obtained by performing image acquisition on theto-be-verified certificate under different acquisition conditions;obtaining, from the at least two images, a target image(s) thatcorresponds to the at least two images and that includes a coatingfeature, where the coating feature includes an image feature of alight-reflecting characteristic of a coating of the to-be-verifiedcertificate in a corresponding image; and determining, based on thetarget image(s) corresponding to the at least two images, a probabilitythat the to-be-verified certificate is an original.

An embodiment of the present specification further provides an identityverification electronic device, including the following: at least oneprocessor; and at least one memory communicatively connected to the atleast one processor, where the memory stores an instruction that can beexecuted by the at least one processor, and the instruction is executedby the at least one processor to enable the at least one processor toperform the following operations: acquiring at least two images of anidentity certificate of a to-be-verified object, where the at least twoimages are images obtained by performing image acquisition on theidentity certificate under different acquisition conditions; obtaining,from the at least two images, a first target image(s) that correspondsto the at least two images and that includes a coating feature, wherethe coating feature includes an image feature of a light-reflectingcharacteristic of a coating of the identity certificate in acorresponding image; determining, based on the first target image(s)corresponding to the at least two images, a probability that theidentity certificate is an original; when it is determined that theidentity certificate is an original based on the probability, obtaininga second target image(s) that includes identity information from one ofthe at least two images; verifying the identity information in thesecond target image(s) online to determine authenticity of the identityinformation; and determining authenticity of the identity of theto-be-verified object based on the authenticity of the identityinformation.

The previous at least one technical solution used in the embodiments ofthe present specification can achieve the following beneficial effects:The light-reflecting characteristic of the coating of the certificatecan be used to form the coating feature in the acquired image underdifferent acquisition conditions. Then, image recognition processing canbe performed on the acquired image to determine the possibility that theacquired image comes from the original certificate.

BRIEF DESCRIPTION OF DRAWINGS

To describe technical solutions in embodiments of the presentspecification or in the existing technology more clearly, the followingbriefly describes the accompanying drawings needed for describing theembodiments or the existing technology. Clearly, the accompanyingdrawings in the following descriptions merely show some embodiments ofthe present specification, and a person of ordinary skill in the art canstill derive other drawings from these accompanying drawings withoutcreative efforts.

FIG. 1 is a flowchart illustrating a certificate verification method,according to an embodiment of the present specification;

FIG. 2 is a schematic diagram of verifying a passport in a certificateverification method, according to an embodiment of the presentspecification;

FIG. 3 is a schematic structural diagram illustrating a certificateverification apparatus, according to an embodiment of the presentspecification;

FIG. 4 is a flowchart illustrating an identity verification method,according to an embodiment of the present specification; and

FIG. 5 is a schematic structural diagram illustrating an identityverification apparatus, according to an embodiment of the presentspecification.

DESCRIPTION OF EMBODIMENTS

To make a person skilled in the art better understand the technicalsolutions in the present specification, the following clearly describesthe technical solutions in the embodiments of the present specificationwith reference to the accompanying drawings in the embodiments of thepresent specification. Clearly, the described embodiments are merelysome but not all of the embodiments of the present specification. Allother embodiments obtained by a person of ordinary skill in the artbased on the embodiments of the present specification without creativeefforts shall fall within the protection scope of the presentapplication.

As described above, because the process of photographing the uploadedphotos cannot be effectively monitored, vulnerabilities that are easilyattacked are left in the electronic authentication process. However, inthe existing solutions, the photos shot and uploaded by black industryusers by using forged certificates cannot be recognized and easily causedeception. In addition, large-scale data processing needs to beperformed later to recognize the photos before authenticity of thecertificate is determined, resulting in low authentication efficiency.

In view of the previous description, embodiments of the presentspecification provide methods, apparatuses, and devices for certificateverification and identity verification. In one certificate verificationmethod, at least two images of a certificate are acquired, and the atleast two images are obtained by performing image acquisition on thecertificate under different acquisition conditions, respectively. Insuch case, under different acquisition conditions, a light-reflectingcharacteristic of a coating of the certificate forms a correspondingcoating feature in the certificate image. The coating feature includesan image feature of the light-reflecting characteristic of the coatingof the to-be-verified certificate in the corresponding image, so that apossibility that the obtained certificate image comes from an originalcertificate can be determined based on the coating featurescorresponding to the at least two certificate images.

If the certificate is an original, the light-reflecting characteristicof the coating of the certificate forms the coating feature in the atleast two certificate images, and then the probability that thecertificate is an original can be determined by determining the coatingfeature in the image. On the contrary, if the coating of the certificateis missing, for example, the certificate is a certificate obtained bypresenting a forged electronic certificate physically, for example,displaying the forged electronic certificate on a screen or by printing.In such case, because the at least two certificate images are obtainedby photographing the forged electronic certificate, and the photographedforged electronic certificate does not carry the original coating of thecertificate, there is no corresponding coating feature in the at leasttwo certificate images. Therefore, a probability that the certificate isnot an original can be determined based on the fact that there is nocoating feature in the at least two certificate images. Alternatively,the certificate is a forged physical certificate, for example,information on the original certificate is modified. In such case, whenthe information on the original certificate is modified, thelight-reflecting characteristic of the original coating of thecertificate during image acquisition can be damaged, and there will bean intermittent coating feature in the at least two certificate images.In such case, the probability that the certificate is not an originalcan be determined based on the intermittent coating feature in the atleast two certificate images.

The following describes in detail the technical solutions provided inthe embodiments of the present application with reference to theaccompanying drawings.

FIG. 1 is a flowchart illustrating a certificate verification method,according to an embodiment of the present specification.

As shown in FIG. 1, the certificate verification method can include thefollowing steps:

S102: Acquire at least two images of a to-be-verified certificate, wherethe at least two images are images obtained by performing imageacquisition on the to-be-verified certificate under differentacquisition conditions.

In one embodiment, an image acquisition device acquires the image of theto-be-verified certificate. The acquisition condition is used to enablethe light-reflecting characteristic of the coating of the certificate toform the corresponding coating feature in the acquired image.

In an embodiment, the acquisition condition can include an acquisitionangle. For example, acquisition is performed multiple times at differentangles between an acquisition direction of the image acquisition deviceand a normal line of the certificate. For example, acquisition isperformed first when the acquisition direction is perpendicular to thecertificate (i.e., the acquisition angle is zero), and then acquisitionis performed at an oblique angle, so that acquired images of differentangles are obtained. Due to the different acquisition angles, the lightforms different reflection effects (i.e., the light-reflectingcharacteristics) on the coating of the certificate during acquisition,so that the acquired images have the corresponding coating feature. Inother words, if the certificate is an original, the at least two imagesacquired at different angles all include the coating feature. If thecertificate is not an original, because the certificate does not havethe original coating, the at least two images acquired at differentangles either have no coating feature, or have an incomplete coatingfeature, such as an intermittent coating feature.

In another embodiment, the acquisition condition can include anacquisition environment. For example, light conditions in theacquisition environment are different. In such case, because of thedifferent ambient light, the light-reflecting characteristics of thecoating of the certificate also form corresponding coating features inthe acquired images. In other words, if the certificate is an original,because the certificate has the original coating, the at least twoimages acquired in acquisition environments of different light allinclude the coating feature. If the certificate is not an original,because the certificate does not have the original coating, the at leasttwo images acquired under different light conditions either have nocoating feature, or have an incomplete coating feature, such as anintermittent coating feature.

In one embodiment, an acquisition user can also be prompted, forexample, by using a tone to perform acquisition operations underdifferent conditions by using the image acquisition device.

In still another embodiment, because the video stream is usuallyacquired under multiple acquisition conditions such as different time,different acquisition angles, and different ambient light, and canprovide more frames of acquired images, the at least two images of theto-be-verified certificate can also be extracted from the obtained videostream of the to-be-verified certificate. As such, the acquisitiondemands are reduced, the sources of the acquired images can bebroadened, and the at least two images can be selected from more framesof images.

S104: Obtain the target images that correspond to the at least twoimages and that include a coating feature from the at least two images.

The coating feature includes an image feature of a light-reflectingcharacteristic of a coating of the to-be-verified certificate in acorresponding image.

In one embodiment, in the step of obtaining the coating featurecorresponding to the at least two images, some image preprocessing, suchas binarization, alignment, feature detection, etc. can be performedbased on the at least two images. As such, after the preprocessing, atarget image(s) that clearly includes the coating feature and is easy toprocess can be obtained, thereby improving verification efficiency andaccuracy.

In an embodiment, the preprocessing can include image alignmentprocessing. For example, the alignment processing includes searching fora location of a certificate in an image, and performing operations suchas rotating, zooming, and clipping on the certificate in the image.Then, a certificate image after alignment processing is obtained fromthe at least two images. Here, the certificate image is an imageincluded in a certificate boundary. As such, based on the alignedcertificate image, processing of the image portion outside thecertificate boundary can be omitted, and later processing isfacilitated, thereby improving the verification efficiency and accuracy.

It is worthwhile to note that, the image alignment processing can beperformed based on the characteristics of the certificate, and detailsare omitted here for simplicity.

In another embodiment, the preprocessing can include binarizationprocessing, and the binarization processing can include dynamicbinarization processing, or can include binarization processing based ona deep learning model. Because the coating feature is an image featureformed by the light-reflecting characteristic of the coating of thecertificate in the image, after binarization, the coating feature isclearly presented in the at least two images. The image content otherthan the image content formed by the light-reflecting characteristic ofthe coating of the certificate becomes a background value afterbinarization. As such, a large amount of background value processingcontent can be omitted, thereby reducing the performance demand of theverification device and improving verification efficiency and accuracy.

It is worthwhile to note that, the binarization processing can bethreshold binarization such as dynamic binarization and fixed thresholdbinarization, or can be binarization processing based on a deep learningmodel. Details are omitted here for simplicity.

In still another embodiment, detection can be performed based on thecoating feature of the certificate to determine whether the at least twoimages include the coating feature. As such, later processing is stoppedwhen it is detected that the coating feature is not included. The stepof obtaining the target image(s) that includes a coating feature fromthe at least two images includes the following: detecting, based on apredetermined coating feature area, whether there is a coating featurecorresponding to the coating feature area in the at least two images;and if yes, obtaining the target image(s) that includes a coatingfeature from the at least two images. Certainly, if there is no coatingfeature in the at least two images, the later verification processingcan be stopped, or the operation is cleared, for example, the operationis returned to S102 to perform a verification operation again.

In one embodiment, image operators such as scale-invariant featuretransform (SIFT) and speeded up robust feature (SURF) can be used todetermine whether there is a coating feature in the at least two images.

S106: Determine, based on the target image(s) corresponding to the atleast two images, a probability that the to-be-verified certificate isan original.

In one embodiment, the coating feature in the target images can benormalized based on the target images corresponding to the at least twoimages, depending on an actual processing demand. Then, the probabilitythat the to-be-verified certificate is an original is determined basedon the predetermined decision policy and the normalized value of thecoating feature. The decision policy can be a decision relationshipbetween the normalized value of the coating feature and the probabilitythat the certificate is an original.

In an embodiment, the coating feature can be first extracted directlyfrom the target images. Then, the values of the coating featurescorresponding to the target images corresponding to the at least twoimages are calculated, and the values of the coating featurescorresponding to the target images are summed up and normalized.Finally, the probability that the to-be-verified certificate is anoriginal is determined based on the normalized value of the coatingfeature and the predetermined decision policy.

In another embodiment, the target images corresponding to the at leasttwo images can be first divided into areas for feature extraction, forexample, divided into N areas. Then every two areas are compared toobtain N comparison scores, and then the N comparison scores are summedup and normalized. Finally, the probability that the to-be-verifiedcertificate is an original is determined based on the normalized valueof the coating feature and the predetermined decision policy.

It is worthwhile to note that, in the embodiment of the presentspecification, the probability that the to-be-verified certificate is anoriginal is described. Certainly, the probability that theto-be-verified certificate is a forged certificate is obtained after theprobability that the to-be-verified certificate is an original isobtained.

In one embodiment, the probability that the certificate is an originalcan be determined depending on an actual application demand. Then, basedon mapping relationships between the probability, the originalcertificate, the forged electronic certificate, and the forged physicalcertificate, it can be further determined whether the certificate is theoriginal certificate, or whether the certificate is the forgedelectronic certificate or the forged physical certificate. Details areomitted here for simplicity.

In another embodiment, image features of specific areas of thecertificate can also be processed to prevent these areas from beingeasily interfered by binarized results, such as face photo or metal chipparts. Because the locations of these parts relative to the certificateare definite, the image features of these areas can be processedseparately, or the values of the image features of these areas can beexcluded in advance, so as to reduce possible impact of the imagefeature values of these areas in later processing.

In the previous steps S102 to S106, because the coating of thecertificate has the light-reflecting characteristic, and can formcoating features in images acquired under different acquisitionconditions, the images of the to-be-verified certificate under differentacquisition conditions can be obtained first, and then the targetimage(s) that includes the coating feature can be obtained from theacquired images. Finally, the coating feature in the target image(s) isdetermined to determine the probability that the to-be-verifiedcertificate is an original. As such, the probability that theto-be-verified certificate is an original can be identified accuratelyand quickly, efficiency and accuracy of certificate verification can beimproved, and deception of the forged certificate can be prevented basedon the probability.

For ease of understanding, the following describes a schematic processof certificate verification.

FIG. 2 illustrates a process of verifying a passport certificate.

First, the original passport is placed under two acquisition conditionsto acquire corresponding images. For example, the original certificateis placed in front of a background picture, and image 1 is acquired. Theimage result is shown in (a) in the figure. Then the originalcertificate is held in a hand, and image 2 is acquired. The image resultis shown in (e) in the figure. In such case, because the passport is anoriginal, a light-reflecting characteristic of a coating of thecertificate forms coating features in image 1 and image 2, as shown indashed-line blocks in (a) and (e) in the figure, respectively. There areclear coating features in both image 1 and image 2.

Next, target images that include these coating features are obtained.

Specifically, image 1 and image 2 can be aligned first, so thatredundant background parts beyond the certificate range are removed andthe certificate images are aligned. As such, aligned images of the samesize can be obtained. Alignment results of image 1 and image 2 are shownin (b) and (0 in the figure, respectively. Then, the aligned images arebinarized. Here, dynamic binarization processing is performed, and imagefeatures other than the image features formed by the light-reflectingcharacteristic of the coating of the certificate in the images are usedas background values for processing. After the binarization, the coatingfeature results are shown in dashed-line blocks in (c) and (g) in thefigure, respectively. Here, for ease of reading and identification, thecolor of the background values is adjusted from black to white. It canbe seen from (c) and (g) in the figure that, the coating features in theobtained target images are pronounced.

Finally, the probability that the to-be-verified certificate is anoriginal is determined based on the target images corresponding to theat least two images. Here, a target image is divided into N areas, andevery two of the N areas are compared (as indicated by the dashed-linearrows in the figure), and then N comparison scores are obtained. Thenthe N comparison scores are summed up and normalized to obtain thenormalized value of the coating feature. Finally, the probability thatthe passport is an original can be determined based on the decisionpolicy. Here, for ease of description, N is 40, that is, each of thetarget images in (d) and (h) in the figure is divided into 5 rows and 8columns to obtain 40 sub-areas. Then, every one of the 40 sub-areas in(d) and (h) is compared to obtain 40 comparison scores, and the 40comparison scores are summed up and normalized. Finally, the probabilitythat the passport is an original is determined based on the decisionpolicy, which is 99.97%.

Based on the same inventive concept, embodiments of the presentspecification further provide a certificate verification apparatus,electronic device, and a non-volatile computer storage medium.

In consideration of the detailed description of the certificateverification methods in the previous embodiments, the correspondingcontent related to the apparatus, the device, and the non-volatilecomputer storage medium will be omitted in the following embodiments.

FIG. 3 is a schematic structural diagram illustrating a certificateverification apparatus, according to the present specification, wherethe dashed-line block represents an optional module.

As shown in FIG. 3, the certificate verification apparatus 10 includesan image acquisition module 11, an acquisition module 12, and averification module 13. The image acquisition module 11 is configured toacquire at least two images of a to-be-verified certificate, where theat least two images are images obtained by performing image acquisitionon the to-be-verified certificate under different acquisitionconditions. The acquisition module 12 is configured to obtain, from theat least two images, a target image(s) that corresponds to the at leasttwo images and that includes a coating feature, where the coatingfeature includes an image feature of a light-reflecting characteristicof a coating of the to-be-verified certificate in a corresponding image.The verification module 13 is configured to determine, based on thetarget image(s) corresponding to the at least two images, a probabilitythat the to-be-verified certificate is an original.

In some embodiments, in the certificate verification apparatus 10, theacquisition conditions can include at least one of an acquisition angleand an acquisition environment.

In some embodiments, the image acquisition module 11 is configured toobtain the at least two images from a video stream corresponding to theto-be-verified certificate.

In some embodiments, the certificate verification apparatus 10 furtherincludes a binarization module 14. The binarization module 14 isconfigured to perform image binarization processing on the at least twoimages to obtain a binarized image corresponding to the at least twoimages. The acquisition module 12 is configured to obtain the targetimages that correspond to the at least two images and that include acoating feature from the binarized image.

In some embodiments, the certificate verification apparatus 10 furtherincludes an alignment module 15. The alignment module 15 is configuredto perform image alignment processing on the at least two images. Theacquisition module 12 is configured to obtain the target images thatcorrespond to the at least two images and that include a coating featurefrom the at least two images after alignment processing.

In some embodiments, the certificate verification apparatus 10 furtherincludes a detection module 16. The detection module 16 is configured todetect, based on a predetermined coating feature area, whether there isa coating feature corresponding to the coating feature area in the atleast two images, and if yes, invoke the acquisition module 12. Theacquisition module is configured to obtain the target images thatcorrespond to the at least two images and that include a coating featurefrom the at least two images.

In some embodiments, the certificate verification apparatus 10 furtherincludes a normalization module 17. The normalization module 17 isconfigured to perform normalization processing on the target imagescorresponding to the at least two images to obtain a normalized value ofthe coating feature. The verification module 13 is configured todetermine, based on the normalized value of the coating feature and apredetermined decision policy, the probability that the to-be-verifiedcertificate is an original, where the decision policy includes adecision relationship between the normalized value of the coatingfeature and the probability that the certificate is an original.

An embodiment of the present specification further provides acertificate verification electronic device, including the following: atleast one processor; and at least one memory communicatively connectedto the at least one processor, where the memory stores an instructionthat can be executed by the at least one processor, and the instructionis executed by the at least one processor to enable the at least oneprocessor to perform the following operations: acquiring at least twoimages of a to-be-verified certificate, where the at least two imagesare images obtained by performing image acquisition on theto-be-verified certificate under different acquisition conditions;obtaining, from the at least two images, a target image(s) thatcorresponds to the at least two images and that includes a coatingfeature, where the coating feature includes an image feature of alight-reflecting characteristic of a coating of the to-be-verifiedcertificate in a corresponding image; and determining, based on thetarget image(s) corresponding to the at least two images, a probabilitythat the to-be-verified certificate is an original.

An embodiment of the present specification further provides anon-volatile computer storage medium for certificate verification, wherethe non-volatile computer storage medium stores a computer executableinstruction, and the computer executable instruction is set to performthe following operations: acquiring at least two images of ato-be-verified certificate, where the at least two images are imagesobtained by performing image acquisition on the to-be-verifiedcertificate under different acquisition conditions; obtaining, from theat least two images, a target image(s) that corresponds to the at leasttwo images and that includes a coating feature, where the coatingfeature includes an image feature of a light-reflecting characteristicof a coating of the to-be-verified certificate in a corresponding image;and determining, based on the target image(s) corresponding to the atleast two images, a probability that the to-be-verified certificate isan original.

Based on the same inventive concept, embodiments of the presentspecification further provide an identity verification method,apparatus, and device.

FIG. 4 is a flowchart illustrating an identity verification method,according to an embodiment of the present specification. The identityverification method can include the following steps:

S202: Acquire at least two images of an identity certificate of ato-be-verified object, where the at least two images are images obtainedby performing image acquisition on the identity certificate underdifferent acquisition conditions.

The identity certificate can include a certificate that can prove anidentity of the to-be-verified object, such as a passport, an identitycard, a driver's license, etc. The surface of the identity certificatefurther records identity information of the to-be-verified object, suchas a name, a sex, an identity card number, etc.

S204: Obtain, from the at least two images, a first target image(s) thatcorresponds to the at least two images and that includes a coatingfeature, where the coating feature includes an image feature of alight-reflecting characteristic of a coating of the identity certificatein a corresponding image.

S206: Determine, based on the first target image(s) corresponding to theat least two images, a probability that the identity certificate is anoriginal.

S208: Determine, based on the probability that the identity certificateis an original, whether the identity certificate is an original, and ifyes, perform S210.

It is worthwhile to note that, in the step of determining whether theidentity certificate is an original, the determining result can befurther output by using a prompt such as a voice or a text. When it isdetermined that the identity certificate is not an original, theoperation can be cleared, for example, the operation returns to S202.

S210: Obtain a second target image(s) that includes identity informationfrom one of the at least two images.

S212: Verify the identity information in the second target image(s)online to determine an authenticity level of the identity information.

S214: Determine authenticity of the identity of the to-be-verifiedobject based on the authenticity level of the identity information.

It is worthwhile to note that, the content of steps S202 to S206 issimilar to the content of steps S102 to S106 of the certificateverification method described in the previous embodiment, and detailsare omitted here for simplicity.

In the previous steps S202 to S214, because the light-reflectingcharacteristic of the coating of the identity certificate can form thecorresponding coating features in the acquired images under differentacquisition conditions, it can be accurately and quickly determinedwhether the identity certificate of the to-be-verified object is anoriginal, and then the authenticity level of the identity informationcan be verified online when the identity certificate is an original, andthe authenticity of the identity of the to-be-verified object can bedetermined based on the online verification result. As such, accuracyand efficiency of identity verification are improved, and deception ofthe forged certificate during electronic authentication can beeffectively prevented based on the identity result of the to-be-verifiedobject.

In consideration of the detailed description of the identityverification method in the previous embodiments, the correspondingcontent related to the identity verification apparatus, device, andnon-volatile computer storage medium will be omitted in the followingembodiments.

FIG. 5 is a schematic structural diagram illustrating an identityverification apparatus, according to an embodiment of the presentspecification.

As shown in FIG. 5, the identity verification apparatus 20 includes animage acquisition module 21, a first acquisition module 22, a firstverification module 23, a second acquisition module 24, a networkingmodule 25, and a second verification module 26. The image acquisitionmodule 21 is configured to acquire at least two images of an identitycertificate of a to-be-verified object, where the at least two imagesare images obtained by performing image acquisition on the identitycertificate under different acquisition conditions. The firstacquisition module 22 is configured to obtain, from the at least twoimages, a first target image(s) that corresponds to the at least twoimages and that includes a coating feature, where the coating featureincludes an image feature of a light-reflecting characteristic of acoating of the identity certificate in a corresponding image. The firstverification module 23 is configured to determine, based on the firsttarget image(s) corresponding to the at least two images, a probabilitythat the identity certificate is an original. The second acquisitionmodule 24 is configured to: when it is determined that the identitycertificate is an original based on the probability, obtain a secondtarget image(s) that includes identity information from one of the atleast two images. The networking module 25 is configured to verify theidentity information in the second target image(s) online to determineauthenticity of the identity information. The second verification module26 is configured to determine authenticity of the identity of theto-be-verified object based on the authenticity of the identityinformation.

An embodiment of the present specification further provides an identityverification electronic device, including the following: at least oneprocessor; and at least one memory communicatively connected to the atleast one processor, where the memory stores an instruction that can beexecuted by the at least one processor, and the instruction is executedby the at least one processor to enable the at least one processor toperform the following operations: acquiring at least two images of anidentity certificate of a to-be-verified object, where the at least twoimages are images obtained by performing image acquisition on theidentity certificate under different acquisition conditions; obtaining,from the at least two images, a first target image(s) that correspondsto the at least two images and that includes a coating feature, wherethe coating feature includes an image feature of a light-reflectingcharacteristic of a coating of the identity certificate in acorresponding image; determining, based on the first target image(s)corresponding to the at least two images, a probability that theidentity certificate is an original; when it is determined that theidentity certificate is an original based on the probability, obtaininga second target image(s) that includes identity information from one ofthe at least two images; verifying the identity information in thesecond target image(s) online to determine authenticity of the identityinformation; and determining authenticity of the identity of theto-be-verified object based on the authenticity of the identityinformation.

An embodiment of the present specification further provides anon-volatile computer storage medium for identity verification, wherethe non-volatile computer storage medium stores a computer executableinstruction, and the computer executable instruction is set to performthe following operations: acquiring at least two images of an identitycertificate of a to-be-verified object, where the at least two imagesare images obtained by performing image acquisition on the identitycertificate under different acquisition conditions; obtaining, from theat least two images, a first target image(s) that corresponds to the atleast two images and that includes a coating feature, where the coatingfeature includes an image feature of a light-reflecting characteristicof a coating of the identity certificate in a corresponding image;determining, based on the first target image(s) corresponding to the atleast two images, a probability that the identity certificate is anoriginal; when it is determined that the identity certificate is anoriginal based on the probability, obtaining a second target image(s)that includes identity information from one of the at least two images;verifying the identity information in the second target image(s) onlineto determine authenticity of the identity information; and determiningauthenticity of the identity of the to-be-verified object based on theauthenticity of the identity information.

Some embodiments of the present specification are described above. Otherembodiments fall within the scope of the appended claims. In somesituations, the actions or steps described in the claims can beperformed in an order different from the order in the embodiments andthe desired results can still be achieved. In addition, the processdepicted in the accompanying drawings does not necessarily need aparticular execution order to achieve the desired results. In someembodiments, multi-tasking and concurrent processing is feasible or canbe advantageous.

The embodiments in the present specification are described in aprogressive way. For same or similar parts of the embodiments,references can be made to the embodiments mutually. Each embodimentfocuses on a difference from other embodiments. Especially, an apparatusembodiment, a device embodiment, a non-volatile computer storage mediumembodiment are similar to a method embodiment, and therefore aredescribed briefly. For related parts, references can be made to thedescriptions in the method embodiment.

The apparatus, the device, and the non-volatile computer storage mediumprovided in the embodiments of the present specification correspond tothe method. Therefore, the apparatus, the device, and the non-volatilecomputer storage medium also have beneficial technical effects similarto those of the corresponding method. The beneficial technical effectsof the method are described in detail above, so the beneficial technicaleffects of the corresponding apparatus, device, and non-volatilecomputer storage medium are omitted here.

In the 1990s, whether a technical improvement is a hardware improvement(for example, an improvement to a circuit structure, such as a diode, atransistor, or a switch) or a software improvement (an improvement to amethod procedure) can be clearly distinguished. However, as technologiesdevelop, current improvements to many method procedures can beconsidered as direct improvements to hardware circuit structures. Adesigner usually programs an improved method procedure into a hardwarecircuit, to obtain a corresponding hardware circuit structure.Therefore, a method procedure can be improved by using a hardware entitymodule. For example, a programmable logic device (PLD) (for example, afield programmable gate array (FPGA)) is such an integrated circuit, anda logical function of the PLD is determined by a user through deviceprogramming. The designer performs programming to “integrate” a digitalsystem to a PLD without requesting a chip manufacturer to design andproduce an application-specific integrated circuit chip. In addition, atpresent, instead of manually manufacturing an integrated chip, this typeof programming is mostly implemented by using “logic compiler” software.The programming is similar to a software compiler used to develop andwrite a program. Original code needs to be written in a particularprogramming language for compilation. The language is referred to as ahardware description language (HDL). There are many HDLs, such as theAdvanced Boolean Expression Language (ABEL), the Altera HardwareDescription Language (AHDL), Confluence, the Cornell UniversityProgramming Language (CUPL), HDCal, the Java Hardware DescriptionLanguage (JHDL), Lava, Lola, MyHDL, PALASM, and the Ruby HardwareDescription Language (RHDL). The very-high-speed integrated circuithardware description language (VHDL) and Verilog are most commonly used.A person skilled in the art should also understand that a hardwarecircuit that implements a logical method procedure can be readilyobtained once the method procedure is logically programmed by using theseveral described hardware description languages and is programmed intoan integrated circuit.

A controller can be implemented by using any appropriate method. Forexample, the controller can be a microprocessor or a processor, or acomputer-readable medium that stores computer readable program code(such as software or firmware) that can be executed by themicroprocessor or the processor, a logic gate, a switch, anapplication-specific integrated circuit (ASIC), a programmable logiccontroller, or a built-in microprocessor. Examples of the controllerinclude but are not limited to the following microprocessors: ARC 625D,Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320. Thememory controller can also be implemented as a part of the control logicof the memory. A person skilled in the art also knows that, in additionto implementing the controller by using the computer readable programcode, logic programming can be performed on method steps to allow thecontroller to implement the same function in forms of the logic gate,the switch, the application-specific integrated circuit, theprogrammable logic controller, and the built-in microcontroller.Therefore, the controller can be considered as a hardware component, andan apparatus configured to implement various functions in the controllercan also be considered as a structure in the hardware component. Or theapparatus configured to implement various functions can even beconsidered as both a software module implementing the method and astructure in the hardware component.

The system, apparatus, module, or unit illustrated in the previousembodiments can be implemented by using a computer chip or an entity, orcan be implemented by using a product having a certain function. Atypical implementation device is a computer. The computer can be, forexample, a personal computer, a laptop computer, a cellular phone, acamera phone, a smart phone, a personal digital assistant, a mediaplayer, a navigation device, an e-mail device, a game console, a tabletcomputer, a wearable device, or a combination of any of these devices.

For ease of description, the previous apparatus is described by dividingfunctions into various units. Certainly, when the present application isimplemented, a function of each unit can be implemented in one or morepieces of software and/or hardware.

A person skilled in the art should understand that the embodiments ofthe present disclosure can be provided as a method, a system, or acomputer program product. Therefore, the present disclosure can use aform of hardware only embodiments, software only embodiments, orembodiments with a combination of software and hardware. Moreover, thepresent disclosure can use a form of a computer program product that isimplemented on one or more computer-usable storage media (including butnot limited to a magnetic disk memory, a CD-ROM, and an optical memory)that include computer-usable program code.

The present disclosure is described with reference to the flowchartsand/or block diagrams of the method, the device (system), and thecomputer program product according to the embodiments of the presentdisclosure. It is worthwhile to note that computer program instructionscan be used to implement each process and/or each block in theflowcharts and/or the block diagrams and a combination of a processand/or a block in the flowcharts and/or the block diagrams. Thesecomputer program instructions can be provided for a general-purposecomputer, a dedicated computer, an embedded processor, or a processor ofanother programmable data processing device to generate a machine, sothe instructions executed by the computer or the processor of theanother programmable data processing device generate a device forimplementing a specific function in one or more processes in theflowcharts and/or in one or more blocks in the block diagrams.

These computer program instructions can be stored in a computer readablememory that can instruct the computer or the another programmable dataprocessing device to work in a specific way, so the instructions storedin the computer readable memory generate an artifact that includes aninstruction apparatus. The instruction apparatus implements a specificfunction in one or more processes in the flowcharts and/or in one ormore blocks in the block diagrams.

These computer program instructions can be loaded onto the computer oranother programmable data processing device, so a series of operationsand steps are performed on the computer or the another programmabledevice, thereby generating computer-implemented processing. Therefore,the instructions executed on the computer or the another programmabledevice provide steps for implementing a specific function in one or moreprocesses in the flowcharts and/or in one or more blocks in the blockdiagrams.

In a typical configuration, a computing device includes one or moreprocessors (CPUs), one or more input/output interfaces, one or morenetwork interfaces, and one or more memories.

The memory can include a non-persistent memory, a random access memory(RAM), a non-volatile memory, and/or another form that are in a computerreadable medium, for example, a read-only memory (ROM) or a flash memory(flash RAM). The memory is an example of the computer readable medium.

The computer readable medium includes persistent, non-persistent,movable, and unmovable media that can store information by using anymethod or technology. The information can be a computer readableinstruction, a data structure, a program module, or other data. Examplesof the computer storage medium include but are not limited to a phasechange random access memory (PRAM), a static RAM (SRAM), a dynamic RAM(DRAM), a RAM of another type, a read-only memory (ROM), an electricallyerasable programmable ROM (EEPROM), a flash memory or another memorytechnology, a compact disc ROM (CD-ROM), a digital versatile disc (DVD),or another optical storage, a cassette, a cassette magnetic diskstorage, or another magnetic storage device or any othernon-transmission medium. The computer storage medium can be configuredto store information that can be accessed by a computing device. Basedon the definition in the present specification, the computer readablemedium does not include transitory media such as a modulated data signaland carrier.

It is worthwhile to further note that, the terms “include”, “contain”,or their any other variants are intended to cover a non-exclusiveinclusion, so a process, a method, a product or a device that includes alist of elements not only includes those elements but also includesother elements which are not expressly listed, or further includeselements inherent to such process, method, product or device. Withoutmore constraints, an element preceded by “includes a . . . ” does notpreclude the existence of additional identical elements in the process,method, product or device that includes the element.

The present application can be described in the general context ofexecutable computer instructions executed by a computer, for example, aprogram module. Generally, the program module includes a routine, aprogram, an object, a component, a data structure, etc. executing aspecific task or implementing a specific abstract data type. The presentapplication can alternatively be practiced in distributed computingenvironments in which tasks are performed by remote processing devicesthat are connected through a communications network. In a distributedcomputing environment, the program module can be located in both localand remote computer storage media including storage devices.

The previous descriptions are merely embodiments of the presentapplication, and are not intended to limit the present application. Aperson skilled in the art can make various modifications and changes tothe present application. Any modification, equivalent replacement, orimprovement made without departing from the spirit and principle of thepresent application shall fall within the scope of the claims in thepresent application.

1.-21. (canceled)
 22. A computer-implemented certificate verificationmethod, comprising: obtaining at least two images of a certificate,wherein the at least two images are acquired under different acquisitionconditions; obtaining, from the at least two images, at least two targetimages that correspond to respective images of the at least two imagesand that each comprise an image of a light-reflective coating of thecertificate; extracting values corresponding to the light-reflectivecoating from the at least two target images; and determining, based onthe extracted values corresponding to the light-reflective coating fromthe at least two target images, that the certificate is authentic orthat the certificate is inauthentic.
 23. The computer-implemented methodof claim 22, wherein the different acquisition conditions comprise atleast one of: different acquisition angles and different lightingenvironments.
 24. The computer-implemented method of claim 22, whereinobtaining the at least two images of the certificate comprises:obtaining the at least two images from a video of the certificate. 25.The computer-implemented method of claim 22, wherein obtaining the atleast two target images comprises: performing image binarizationprocessing on the at least two images to obtain binarized imagescorresponding to the at least two images; and obtaining the at least twotarget images from the binarized images.
 26. The computer-implementedmethod of claim 22, wherein obtaining the at least two target imagescomprises: performing image alignment processing on the at least twoimages to obtained aligned images corresponding to the at least twoimages; and obtaining the at least two target images from the alignedimages.
 27. The computer-implemented method of claim 22, whereindetermining that the certificate is authentic or that the certificate isinauthentic comprises: dividing each of the at least two target imagesinto areas; comparing corresponding areas between the at least twotarget images, to obtain comparison scores; and determining, based onthe comparison scores, that the certificate is authentic or that thecertificate is inauthentic.
 28. The computer-implemented method of claim22, wherein determining that the certificate is authentic or that thecertificate is inauthentic comprises: performing normalizationprocessing on the extracted values to obtain a normalized valuecorresponding to the light-reflective coating; and determining, based onthe normalized value and a predetermined decision policy, that thecertificate is authentic or that the certificate is inauthentic, whereinthe predetermined decision policy comprises a decision relationshipbetween the normalized value and a decision that the certificate isauthentic or inauthentic.
 29. A non-transitory, computer-readable mediumstoring one or more instructions that, when executed by a computersystem, cause the computer system to perform operations comprising:obtaining at least two images of a certificate, wherein the at least twoimages are acquired under different acquisition conditions; obtaining,from the at least two images, at least two target images that correspondto respective images of the at least two images and that each comprisean image of a light-reflective coating of the certificate; extractingvalues corresponding to the light-reflective coating from the at leasttwo target images; and determining, based on the extracted valuescorresponding to the light-reflective coating from the at least twotarget images, that the certificate is authentic or that the certificateis inauthentic.
 30. The computer-readable medium of claim 29, whereinthe different acquisition conditions comprise at least one of: differentacquisition angles and different lighting environments.
 31. Thecomputer-readable medium of claim 29, wherein obtaining the at least twoimages of the certificate comprises: obtaining the at least two imagesfrom a video of the certificate.
 32. The computer-readable medium ofclaim 29, wherein obtaining the at least two target images comprises:performing image binarization processing on the at least two images toobtain binarized images corresponding to the at least two images; andobtaining the at least two target images from the binarized images. 33.The computer-readable medium of claim 29, wherein obtaining the at leasttwo target images comprises: performing image alignment processing onthe at least two images to obtained aligned images corresponding to theat least two images; and obtaining the at least two target images fromthe aligned images.
 34. The computer-readable medium of claim 29,wherein determining that the certificate is authentic or that thecertificate is inauthentic comprises: dividing each of the at least twotarget images into areas; comparing corresponding areas between the atleast two target images, to obtain comparison scores; and determining,based on the comparison scores, that the certificate is authentic orthat the certificate is inauthentic.
 35. The computer-readable medium ofclaim 29, wherein determining that the certificate is authentic or thatthe certificate is inauthentic comprises: performing normalizationprocessing on the extracted values to obtain a normalized valuecorresponding to the light-reflective coating; and determining, based onthe normalized value and a predetermined decision policy, that thecertificate is authentic or that the certificate is inauthentic, whereinthe predetermined decision policy comprises a decision relationshipbetween the normalized value and a decision that the certificate isauthentic or inauthentic.
 36. A computer-implemented system, comprising:one or more computers; and one or more computer memory devicesinteroperably coupled with the one or more computers and havingtangible, non-transitory, machine-readable media storing one or moreinstructions that, when executed by the one or more computers, cause theone or more computers to perform one or more operations comprising:obtaining at least two images of a certificate, wherein the at least twoimages are acquired under different acquisition conditions; obtaining,from the at least two images, at least two target images that correspondto respective images of the at least two images and that each comprisean image of a light-reflective coating of the certificate; extractingvalues corresponding to the light-reflective coating from the at leasttwo target images; and determining, based on the extracted valuescorresponding to the light-reflective coating from the at least twotarget images, that the certificate is authentic or that the certificateis inauthentic.
 37. The computer-implemented system of claim 36, whereinthe different acquisition conditions comprise at least one of: differentacquisition angles and different lighting environments.
 38. Thecomputer-implemented system of claim 36, wherein obtaining the at leasttwo images of the certificate comprises: obtaining the at least twoimages from a video of the certificate.
 39. The computer-implementedsystem of claim 36, wherein obtaining the at least two target imagescomprises: performing image binarization processing on the at least twoimages to obtain binarized images corresponding to the at least twoimages; and obtaining the at least two target images from the binarizedimages.
 40. The computer-implemented system of claim 36, whereinobtaining the at least two target images comprises: performing imagealignment processing on the at least two images to obtained alignedimages corresponding to the at least two images; and obtaining the atleast two target images from the aligned images.
 41. Thecomputer-implemented system of claim 36, wherein determining that thecertificate is authentic or that the certificate is inauthenticcomprises: dividing each of the at least two target images into areas;comparing corresponding areas between the at least two target images, toobtain comparison scores; and determining, based on the comparisonscores, that the certificate is authentic or that the certificate isinauthentic.
 42. The computer-implemented system of claim 36, whereindetermining that the certificate is authentic or that the certificate isinauthentic comprises: performing normalization processing on theextracted values to obtain a normalized value corresponding to thelight-reflective coating; and determining, based on the normalized valueand a predetermined decision policy, that the certificate is authenticor that the certificate is inauthentic, wherein the predetermineddecision policy comprises a decision relationship between the normalizedvalue and a decision that the certificate is authentic or inauthentic.